Unpacking Openness: from seemingly transparent to definitely opaque

25 juli 2012

Last month we were honoured to have Nishant Shah visit our office to have a vibrant discussion about the multiple understandings and purposes of the term ‘openness’. Shah is research director of the Indian Centre for Internet and Society (CIS). CIS undertakes interdisciplinary research about knowledge access, openness, transparency and governance in the digital age. Shah spent an hour of his valuable time discussing how openness may be interpreted. Kennisland is also actively promoting openness. Therefore it was interesting to discover how the term is used differently across the world, at least within our discussion in the Netherlands and in Asia.

Shah describes openness as an opaque metaphor. Openness is used as a metaphor or rhetoric tool to achieve or argue for transparency, accountability, efficiency, community building and other changes in governance and structuring civil society.

Openness or technocratic uncovering?

There is not one specific conceptual tool to explain what openness is. Still we use the term openness in different contexts to argue for being moral, good, efficient and transparent. When we decompose the term, we discover that ‘open’ is not necessarily always the equivalent of ‘good’. Shah unpacks this opaque metaphor in terms of transparency and shows us that when a government uses the metaphor of openness for transparency it does not mean that all the data exposed is useful for everyone, produced by everyone, or beneficial for everyone. It can actually mean other perspectives and information are kept hidden or turn invisible at the same time. An almost technocratic uncovering occurs. The perspectives and documents that can be made available through the tools of transparency, like access to statistics and policy, gain importance and become the dominant perspective of ‘progress’.

This makes other perspectives and problems less visible. In China for example many people are being displaced because new cities are being constructed. Documents on these new cities are readily available, but no documents are available on the people who used to live in those areas. This type of selective ‘transparency’ actually makes these displaced people less visible for researchers and policy makers. Likewise, in India transparency is used as a tool for financing and subsidies. But it disrupts the social structures that are already in place to make types of social subsidies possible. In this case a bureaucratic solution has pushed away a social structure that had been around for decades. Consequently openness excluded the most marginalized people who depended on these social structures.

Shah argues for more multi-faceted research on the multiple uses and interpretations of the term openness to uncover situations where openness has its drawbacks. He does not argue that openness is bad or good, but that we need more insights into to the process of openness in seemingly transparent societies.

Openness and what it means to Kennisland

At Kennisland we use the term openness frequently. What does Shah’s proposed argument mean for our activities? In our work openness is not directly geared towards pushing for more governmental transparency but meant to empower citizens to achieve social and sectorial innovations. Kennisland does not directly lobby or petition governments to open up datasets but we believe that more open datasets help empowering citizens to participate more equally in our society. We agree that just opening up data is only a part of this process.

Moreover Kennisland uses openness in a legal rights perspective: openness is content or data that is shared with everyone with permission to re-use and mix, even for commercial purposes. We educate the general public, NGO’s and governments about the opportunities that arise by creating access to copyrighted material. For example, our project opencultuurdata.nl helps archives and museums to open up their collections by creating open data and open content. It is very important for us to stress the point that open data ought to be used as an extra communication channel that needs to be used in addition to already existing communication channels. Simply replacing existing communication channels by open data or open content will lead to the same social problems that Shah revealed.

Below I describe two examples or scenarios in which a group of people holding certain information, or a group of people who do not have access to data, can become marginalized and therefore unheard.

Old vs. young

The Dutch cultural sector, a very innovative sector, needs to keep older generations in mind. It needs to realize that the generation that demands openness in terms of transparency, efficiency, and reuse is a different type of audience: young, fast and tech-savvy. Besides, in the Netherlands the products of openness, in our legal perspective, can also have significant social consequences. In the Netherlands openness is usually connected to the internet and digital access. That means that older, less technologically educated generations can actually lose access to important resources, data and forms. Therefore it is important to serve different generations independently from each other.

Large vs. small

In a second scenario, there is also a risk of a growing cultural bias in favor of the larger cultural institutions. Only these large institutions have now managed to open up their institutions with open data and open content. Only these collections can now be used on Wikipedia, third-party websites and in innovative applications. Smaller cultural institutions experience more difficulties opening up because of several reasons: lack of money, lack of power and therefore access, and lack of knowledge. This could lead to a dominant cultural canon, in which less influential cultural collections are invisible. Luckily we see a lot of national aggregators that fill this gap, like digitalecollectie.nl and Collectie Gelderland.

In our current and future ventures we will keep these important points in mind and we encourage others to do the same by asking the following questions: who is opening data, and for what purpose? And consequently, who isn’t, and why?